Institute of Medical Psychology and Behavioural Neurobiology, University of Tübingen, 72076 Tübingen, Otfried-Müller-Str. 25, Germany.
Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Martinistraße 52, Building N43, Germany.
Neuroimage. 2021 Jan 1;224:117452. doi: 10.1016/j.neuroimage.2020.117452. Epub 2020 Oct 13.
Sleep spindles are crucial to memory consolidation. Cortical gamma oscillations (30-100 Hz) are considered to reflect processing of memory in local cortical networks. The temporal and regulatory relationship between spindles and gamma activity might therefore provide clues into how sleep strengthens cortical memory representations. Here, combining EEG with MEG recordings during sleep in healthy humans (n = 12), we investigated the temporal relationships of cortical gamma band activity, always measured by MEG, during fast (12-16 Hz) and slow (8-12 Hz) sleep spindles detected in the EEG or MEG. Time-frequency distributions did not show a consistent coupling of gamma to the spindle oscillation, although activity in the low gamma (30-40 Hz) and neighboring beta range (<30 Hz) was generally increased during spindles. However, more fine-grained analyses of cross-frequency interactions revealed that both low and high gamma power (30-100 Hz) was coupled to the phase of slow and fast EEG spindles, importantly, with this coupling at a fixed phase only for the oscillations within an individual spindle, but with variable phase across spindles. We did not observe any coupling of gamma activity for spindles detected solely in the MEG and not in parallel EEG recordings, raising the possibility that these are more local spindles of different quality. Similar to fast spindle activity, low gamma band power followed a ~0.025 Hz infraslow rhythm during sleep whose frequency, however, was significantly faster than that of spindle activity. Our findings suggest a general function of fast and slow spindles that by spanning larger cortical networks might serve to synchronize gamma band activity occurring in more local but distributed networks. Thereby, spindles might help linking local memory processing between distributed networks.
睡眠梭形波对于记忆巩固至关重要。皮质γ 振荡(30-100 Hz)被认为反映了局部皮质网络中记忆的处理。因此,梭形波和γ 活动之间的时间和调节关系可能为我们提供线索,了解睡眠如何增强皮质记忆表现。在这里,我们结合了健康人类睡眠期间的 EEG 和 MEG 记录(n=12),研究了在 EEG 或 MEG 中检测到的快速(12-16 Hz)和慢速(8-12 Hz)睡眠梭形波期间,皮质 γ 波段活动的时间关系,MEG 总是可以测量到γ 波段活动。时频分布并未显示出γ 与纺锤体振荡的一致耦合,尽管纺锤体期间通常会增加低γ(30-40 Hz)和相邻β频带(<30 Hz)的活动。然而,对交叉频率相互作用的更精细分析表明,低γ和高γ功率(30-100 Hz)都与慢和快 EEG 纺锤体的相位耦合,重要的是,这种耦合仅在单个纺锤体的振荡内具有固定相位,但在纺锤体之间具有可变相位。我们没有观察到仅在 MEG 中检测到而不在平行 EEG 记录中检测到的纺锤体的任何γ 活动耦合,这增加了这些是不同质量的更局部纺锤体的可能性。与快速纺锤体活动类似,低γ 频带功率在睡眠期间跟随一个约 0.025 Hz 的次慢节律,但其频率明显快于纺锤体活动的频率。我们的发现表明,快速和慢速纺锤体具有一般功能,通过跨越更大的皮质网络,可能有助于同步发生在更局部但分布更广的网络中的γ 频带活动。因此,纺锤体可能有助于在分布式网络之间连接局部记忆处理。